搜索资源列表
ridgeregresssvm
- 最小二乘支持向量机岭回归函数,可以进行预测和分类-least squares support vector machine regression function Ridge, forecasts and classification
denoise_kpca
- 最小二乘支持向量机岭回归函数,可以进行预测和分类-least squares support vector machine regression function Ridge, forecasts and classification
regrRR
- Ridge Regression RR 岭回归估计，是非常有用的非线性时间序列算法，在局部多项式预测中非常有用。
linghuigui
- 岭回归文章附MATLAB源代码，相对完整，是一篇学生论文。-Ridge Regression article attached to MATLAB source code, relatively complete, is a student paper.
regression_copy
- 岭回归程序 输入参数为自变量、因变量和优化因子 输出参数为映射矩阵与回归误差-Ridge Regression. Input parameters: - X: Input data block (k x n) - Y: Output data block (k x m) - q: Stabiliaztion factor (optional) If not given, estimated from data Return parameters: - F
ridge
- 应用回归分析中岭回归的matlab程序代码-RIDGE REGRESSION
Redge-regression
- 岭回归的matla源程序，主要用于解决无法求逆或需要更好的解时所用的-Ridge regression matla source, mainly used to solve the inverse can not be a better solution or need to use when
RIDGE-REGRESSION
- FORTRAN语言程序。这是进行数理统计上岭回归的计算机程序，很好用的。 -THIS IS A PROGRAM OF RIDGE REGRESSION PROGRAM.
System-Engineering-Algorithm
- 系统工程涉及到的算法的matlab可视化实现，主要有主成分分析、岭回归分析等。-Systems engineering related to the algorithm matlab Visualization, mainly principal component analysis, ridge regression analysis.
SAS6_11linghuiguichengxujishili
- sas学习材料，有关岭回归的程序设计及实例分析，非常详细-sas learning materials, the ridge regression analysis program design and examples, very detailed
rbf.tar
- 线性神经网络 Mark J，L，Orr 子集选择 岭回归-Linear Neural Networks
Fridge-regress
- 岭回归分析（Ridge regression）是一种专用于共线性数据分析的有偏估计回归方法，这套源码是对ridge regression算法的一种实现，附有测试实例-Ridge regression (Ridge regression) is a special collinearity data analysis unbiased estimate of the regression method, this set of source code is an implementation of
mtl_reg_sim_complinearized
- 多元非线性回归——岭回归方法，比常规的最小二乘更适合数据量较大的优化问题-Multiple nonlinear regression- ridge regression method is more suitable than the conventional least squares optimization problem of the large amount of data
linghuigui
- 该程序为岭回归在决策分析中的应用，能够给出最优的各组分的回归系数-The program for the ridge regression in the application of decision analysis, be able to give the best of each component regression coefficients
PLS-RidgeRegression
- 当数据维数相对较高时，普通的最小二乘方法存在计算问题，该文件给出了两种解决方法：PLS和岭回归方法，并可以看出二者效果差异-When the data dimension is relatively high, the ordinary least squares method of calculation problem exists, the document gives two solutions: PLS and ridge regression methods, and results
ridge11
- matlab岭回归分析专用,可供需要人士进行编程实现，本人亲测有效，不过数据需要使用者寻找。-ridge regression analysis matlab exclusively available to those in need for programming, I pro-test effective, but requires users to find the data.
ridgew
- 自己写的岭回归算法。做统计的都懂得。有需要就自己下载-Write your own regression algorithm. All know how to do statistics. There is a need to download
ridgereg
- 岭回归函数，基于SVD分解的岭回归函数，已经证明了是非的有用和强大- center input and output, so we can estimate w0 separately since we don t want to shrink w0
ridge regression1
- 岭回归(英文名：ridge regression, Tikhonov regularization)是一种专用于共线性数据分析的有偏估计回归方法，实质上是一种改良的最小二乘估计法，通过放弃最小二乘法的无偏性，以损失部分信息、降低精度为代价获得回归系数更为符合实际、更可靠的回归方法，对病态数据的拟合要强于最小二乘法。 总之，本文档是岭回归的R语言实现代码，主要用于解决当模型中出现多重共线性问题，尤其是当你所有的解释变量都很重要，又无法通过其他检验来删除时，岭回归是一个很好的解决办法。(Ridge
lasso
- 线性回归里的最小二乘估计，以及应用坐标下降的岭回归和Lasso的回归的python实现(Ridge regression and Lasso regression)